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GPT Multiple Text-Generation

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GPT Multiple Text-Generation

GPT Multiple Text-Generation

possibleapi/gpt-multiple-text-generation

GPT-3.5 Turbo model without OPENAI KEY, provides a robust and user-friendly solution for processing text prompts. This actor is designed to streamline the process, ensuring efficient and high-quality outputs.

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Maintained by Community

You can access the GPT Multiple Text-Generation programmatically from your own applications by using the Apify API. You can also choose the language preference from below. To use the Apify API, you’ll need an Apify account and your API token, found in Integrations settings in Apify Console.

1# Start Server-Sent Events (SSE) session and keep it running
2curl "https://actors-mcp-server.apify.actor/sse?token=<YOUR_API_TOKEN>&actors=possibleapi/gpt-multiple-text-generation"
3
4# Session id example output:
5# event: endpoint
6# data: /message?sessionId=9d820491-38d4-4c7d-bb6a-3b7dc542f1fa

Using Gpt Multiple Text Generation via Model Context Protocol (MCP) server

MCP server lets you use Gpt Multiple Text Generation within your AI workflows. Send API requests to trigger actions and receive real-time results. Take the received sessionId and use it to communicate with the MCP server. The message starts the Gpt Multiple Text Generation Actor with the provided input.

1curl -X POST "https://actors-mcp-server.apify.actor/message?token=<YOUR_API_TOKEN>&session_id=<SESSION_ID>" -H "Content-Type: application/json" -d '{
2  "jsonrpc": "2.0",
3  "id": 1,
4  "method": "tools/call",
5  "params": {
6    "arguments": {},
7    "name": "possibleapi/gpt-multiple-text-generation"
8  }
9}'

The response should be: Accepted. You should received response via SSE (JSON) as:

1event: message
2data: {
3  "result": {
4    "content": [
5      {
6        "type": "text",
7        "text": "ACTOR_RESPONSE"
8      }
9    ]
10  }
11}

Configure local MCP Server via standard input/output for Gpt Multiple Text Generation

You can connect to the MCP Server using clients like ClaudeDesktop and LibreChat or build your own. The server can run both locally and remotely, giving you full flexibility. Set up the server in the client configuration as follows:

1{
2  "mcpServers": {
3    "actors-mcp-server": {
4      "command": "npx",
5      "args": [
6        "-y",
7        "@apify/actors-mcp-server",
8        "--actors",
9        "possibleapi/gpt-multiple-text-generation"
10      ],
11      "env": {
12        "APIFY_TOKEN": "<YOUR_API_TOKEN>"
13      }
14    }
15  }
16}

You can further access the MCP client through the Tester MCP Client, a chat user interface to interact with the server.

To get started, check out the documentation and example clients. If you are interested in learning more about our MCP server, check out our blog post.